Dynamic tracking, analysis and acquisition of e-commerce advertising channels for toll-free and/or telephonic markets

ABSTRACT

The present invention assists the critical real-time decision making required to make important decision on bidding on various customer procurement commodities in a telephonic sales market. The invention provides dynamic pricing as a function of Internet or other types of advertisement costs for the telephonic market. In a preferred embodiment, the present invention is a virtual or physical e-commerce application with an interface connected to the telephonic routing system. A tracking identifier is used with an advertisement, usually a web-based ad, and routed via the vendor to the analysis and procurement system to measure advertising channel effectiveness. A pool of bidders can analyze the tracking data for effective and bid and procure an automated or manual 1800 sales or telephonic call from a consumer based on a number of factors.

REFERENCE TO PRIORITY APPLICATIONS

This Application is a Divisional Application of, and claims priorityunder 35 USC §120 (and §121) to, co-pending U.S. patent application Ser.No. 10/710,852, filed Aug. 7, 2004 and entitled “Dynamic tracking,analysis and acquisition of e-commerce advertising channels fortoll-free markets.” U.S. application Ser. No. 10/710,852 is acontinuation-in-part of and claims priority under 35 USC §120 toco-pending U.S. application Ser. Nos. 10/407,321 and 10/407,323 entitledIntegrated dynamic pricing and procurement support for e-commerceadvertising channels, filed Apr. 4, 2003, which claims priority under 35USC §119(e) to U.S. Provisional Application No. 60/457,794, entitledDynamic margin and pricing decision support tool for customerprocurement transactions, filed Mar. 26, 2003, all of which areincorporated by reference for all purposes.

BACKGROUND ART

A small segment of market share for an e-commerce site/company may meanthe difference between a company going broke and being profitable. Oneof the particular problems with the standard e-commerce transactions nowthat many consumers have high-speed access to the Internet allowing theconsumer to access to an enormous amount of pricing and productinformation over a short period of time that would not have previouslybeen available even with dial-up speeds.

Processing times for Internet graphics and data allow consumers to havemultiple (if not dozens) of screens open at the same time for comparisonshopping. The consumer of such information is based on a much broaderconcept than a purchaser buying a product or service. Thus, drawing thecustomer in to begin with is vital. One of most natural ways to get aconsumer to the passive side is to capture them while they are not surewhere to look on the Internet for something.

Many e-commerce sites use novel transaction techniques to draw customersin to their sites. Quite a variety of Internet and e-commerce techniqueshave been developed over the last decade. Many of them include novelways to sell, buy, trade, barter, negotiate, manage, advertise andpromote over the Internet or other wide area network (WAN). Some exampleInternet e-commerce sites that provide for nontraditional transactionsincludes Ebay.RTM. (timed auctions, immediate purchase),Priceline.com.RTM. (reverse auction, aggregate conditional purchaseoffers U.S. Pat. No. 6,466,919), elimination of a secondary tradechannel (U.S. Pat. No. 6,434,536), and managing the valuation and saleof an aging product inventory (U.S. Pat. No. 6,119,100) assigned toWalker Digital.

Digital Dealing by economist Robert E. Hall (W. W. Norton, 2001) is agood review of the current state of electronic transactions in thebusiness-to-consumer and business-to-business electronic environment. Inparticular, Dr. Hall discusses the various Internet auction systems,which are depicted in a simplified form in FIGS. 1 and 2. This book ishereby incorporated by reference to show the types of transactions andtheir transactional operation for products and services being made overthe Internet.

The increasing need for finding relevant data over the Internet hasproduced a number of categories of data searching techniques andtechnology over wide area networks and in particular the Internet. Manyof these techniques are included in patents and publications provided bywell-known industry leaders in the Internet searching business includingGoogle.TM. and Overture.TM.

Searching techniques may provide searching based on input terms. Theinformation returned to the user may still be inadequate for guidancebecause of the layers of information under an entrance page. Forexample, a large institution such as a government, corporation, ornonprofit organization may easily have more than 100,000 pages ordocuments on one single top-level domain uniform resource locator (URL)and at least a few thousand under a single sublevel. One very popularmethod for keyword searching is the “scoring” method. Google, Inc. ofMountain View, Calif. has several published U.S. Patent Applicationsincluding 2001/0123988 entitled “Methods and Apparatus for EmployingUsage Statistics in Document Retrieval” by Dean et al. and 2001/0133481entitled “Methods and Apparatus for Providing Search Results in Responseto an Ambiguous Search Query.” Google.TM. owns other technology relatedto data searching techniques, for example, a recently issued U.S. Pat.No. 6,526,440 entitled “Ranking Search Results by Reranking the ResultsBased on Local Interconnectivity” by Krishna Bharat, which teaches theuse of connectivity to determine “relevance.” These publications areincorporated by reference as they show the use of keywords in returningsearch results. As can be appreciated, one of the drawbacks of the“scoring” method is that like any statistical method, it can beartificially “skewed” by either a disproportionate group of users orother manipulable techniques. Mechanisms can be put into place toaccount for these factors, the technological advances, and otherwise“skewable” techniques. For example, U.S. Pat. No. 6,269,361 issued toDavis, et al. and assigned to GoTo.com of Pasadena, Calif., describessuch a technique for influencing a place in the list of a search engine.As needed to detail the problem of influencing search results, thisdocument is hereby incorporated by reference.

Promotional literature relating to advertising on search engines andmaximizing its effect are: Successful Keyword Searching: InitiatingResearch on Popular Topics Using Electronic Databases by Randall M.MacDonald and Susan Priest MacDonald; 101 Ways to Boost Your WebTraffic: Internet Promotion Made Easier, 2nd edition by Thomas Wong; andStreetwise Maximize Web Site Traffic: Build Web Site Traffic Fast andFree by Optimizing Search Engine Placement by Robin Nobles and SusanO'Neil. These publications are hereby incorporated by reference toillustrate the operations of search engine marketing techniques.Measuring performance of advertising on the Internet has two problems.The first problem is that the Internet measurement industry is simplygetting used to the appropriate and relevant criteria to measure.Companies such as Nielsen, Gartner Group, and Arbitron have beenmeasuring the “effectiveness” of exposures in traditional media such asradio and television, but applying traditional criteria to Internetadvertising has not been effective. Thus, the more easily measured“number of views” is a particular criterion to which sellers ofadvertising space can point as a pricing system for selling advertisingspace. Companies such as Media Metrix.RTM. have patents such as U.S.Pat. No. 6,115,680 (which is hereby incorporated by reference) currentlyissued to them for placing and measuring advertising on typical Internetsite visit. Other companies such as DoubleClick.RTM. use similartechniques.

The second problem in determining the cost-effectiveness of marketingtools placed over the Internet is interactivity and invasive recording.Simply put, a user of the Internet may view an “impression” on a site.To some degree the placement of “cookies” on a user's computer can helpmeasure the Internet metrics, although tracking consumer behavior afterleaving a site is difficult unless the consumer is consenting toinvasive recording. Another way is “tracking,” which has infuriated manyconsumers who resent that they are being spied on constantly.

The partial solution is to measure or charge by the “click-through.” Theconsumer responds to an advertisement by clicking on a specific link,which redirects their browser or opens a new window to another uniformresource locator (URL). While the tracking is lost, charging by thisbehavior as opposed to what the consumer sees may provide a betterassessment of advertising value. A particularly effective use ofadvertising space is based on search engine criteria, also known in oneaspect as keywords. Keywords are generally natural language search“terms” entered into a search engine site query by a user. The reasonthat keyword advertising may be a better advertising mechanism is thatthe user chooses the type of ads that will be presented as opposed tothe pop-up advertisements that have been compared to junk mail and junkemail (spam). Thus, the Internet advertisement system of click-throughfor keywords is a much more cost related solution.

There are a variety of accounting and data management tools that areimplemented currently which can gather data over the Internet or networkfor an individual or business or consumer transactions. Many of thesetools are implemented by the sellers of the Internet advertisementsthemselves who have a self-interest in analyzing the data in theirfavor.

Often, to lure customers and gain market share, e-commerce companieshave sold items at a loss to gain brand or site recognition. The pricingof items sold over the Internet may have very little to do with actualcost or the desired margin of each item. Furthermore, the cost ofcustomer procurement may seriously vary the profit or loss from eachitem sold and the price of any customer procurement. It has also beensuggested by Martin Bichler in The Future of e-Markets, Chapter 3(Cambridge, 2001) chapter 3, that the Internet pricing models havebecome not only varied but dynamic, the text of which is herebyincorporated by reference. Thus, dynamic pricing makes the relationshipbetween customer procurement over the Internet, performance and profitmargin all the more difficult to determine.

DISCLOSURE OF INVENTION

Because of the above-discussed problems in determining the value ofInternet advertisement and its relation to customer procurement andproduct profitability, it is desirable for e-commerce sellers to havesome type of mechanism to assist them in setting and executing goals forprofit and loss both at a product and a global level and with the speedto make time-critical value decisions about customer procurementpurchases and product pricing. The present invention assists thecritical real-time decision making required to make important decisionon bidding on various customer procurement commodities. The inventionmay also work in reverse by providing dynamic pricing as a function ofInternet advertisement costs. In a preferred embodiment, the presentinvention is a virtual or physical e-commerce application with aninterface. The interface has a global tool and an optional specific toolfor every product that is sold on a particular site. The e-commerce sitehas access to several vital pieces of information which provide theinterface. A net margin is calculated via an import from an accountingpackage or a financial engine (this also may reside as part of thefunctionality of the-e-commerce package) or be a fixed field in the ecommerce package. A real time understanding, of the real cost of a clickthrough or other advertising mechanism at an ad inventory tool whichexists either as an automated tool to login to the Paid Performanceinterface or a field for a static pricing. Other embodiments use pooledperformance data in virtual storage to generate a target price from adesired product margin.

The user can defines much of these factors and then the automated tool,in real time can either change the bid/cost of a procurement of aclick-through or dynamically change of the price of the product toaccommodate the margin desired on a global or product level basis andthe variable expense of advertising. The present invention alsointegrates a dynamically presenting a unique price to the consumer asthe consumer has a history of tolerating a different pricing structure,this can be based on innumerable parameters such as state, zip, title,etc. Also contemplated is integrating and tolerating pricing based onshipping costs tax tables, quantity discounts, or up-selling andcross-selling.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 represents the current art in the acquisition of a customerprocurement device (simple Dutch auction).

FIG. 2 depicts a timed auction mechanisms used over the Internet.

FIG. 3 depicts a basic block diagram of the present invention.

FIG. 4 shows the simplified elements of a user stations.

FIG. 5 represents a block diagram of an embodiment of the e-commerceinterface.

FIG. 6 shows the link between the individual product pricing databases.

FIG. 7 represents an embodiment present invention in a simplified blockdiagram.

FIG. 8 represents a bid delivery system as would be implemented by anembodiment of the present invention (dutch or sealed bid auction).

FIG. 9 represents a bid delivery system as would be implemented by anembodiment of the present invention (english or time-based multiple bidauction).

FIG. 10 shows a method of providing a keyword auction price through anembodiment of the present invention.

FIG. 11 is a flowchart showing a sample method of computing a targetbid.

FIG. 12 represents a grouping of subproducts based on pricingrelationships.

FIG. 13 shows a method for dynamically computing a keyword price.

FIG. 14 shows a method for applying the present invention in atime-based auction.

FIG. 15 represents a method for practicing the multiple search engineembodiment of the invention.

FIG. 16 is a sample contingency relationship table for acquisition ofkeywords over multiple search engine bidding.

FIG. 17 represents a customer procurement device for multiple searchengines and key elements.

FIG. 18 shows a comparison table used in the embodiment of the inventionas shown in FIG. 17.

FIG. 19 depicts a system for analyzing multiple search engines, key wordelements, and permutations.

FIG. 20 shows a simplified resulting relationship table for the systemin FIG. 19.

FIG. 21 illustrates a method for automating the customer procurementdevice bidding and acquisition system.

FIG. 22 is a sample embodiment of the up-selling or cross-sellingembodiment of the present invention.

FIG. 23 is an embodiment of the invention which allows foraffiliate-tracking to determine effective advertising channel placement.

FIG. 24 is a diagram in a telephonic sales channel tracking embodimentof the present invention.

FIG. 25 illustrates a sample comparison tracking method for thetelephonic sales channel supplemental embodiment.

FIG. 26 shows the data flow in telephonic sales advertising channelbidding and routing system for e-commerce advertising channel keywordsin the toll free supplemental embodiment.

FIG. 27 is a representation of the functional aspects of the toll-freeadvertising channel acquisition and routing system.

FIG. 28 is an illustration of a sample ID entry system that may beimplemented at the 1800 vendor level.

MODES FOR THE INVENTION

The following illustrations and descriptions are meant to assist in theunderstanding of the invention and are meant to be representativeexamples of the manner in which the present invention may beimplemented. As such, they are exemplary and not limiting. In apreferred embodiment, the present invention contemplates the key wordauction as the primary method by which the invention will beimplemented. Of course, other customer procurement mechanisms orInternet advertisements and “metrix” are contemplated in alternateembodiments of the invention.

In the following detailed description, components are often referred toin plural.

These components are often numbered as “19(n),” where n is meant toimply an integer or count of the components. Thus, if there are fourdevices for which 19 stands for 19(n) is meant to refer to all items19(1), 19(2), 19(3), and 19(4). The first in a set is referred to 19(a)and the last in a set will be indicated by 19(z). Thus 19(n) willgenerally mean 19(a) . . . 19(z) unless otherwise indicated. Where theremay be singular distinctions made between the plural components, theindividual number (“19(4)”) will be indicated. Where there are intendedto be plural subcomponents of a plural components, the number indicationwill be made as “19(n,n).”

Referring now to FIG. 3, a simplified diagram of a first embodiment ofthe e-commerce interface 100 is shown. The e-commerce interface 100, canbe represented as sitting virtually between the bidder/procurement agentsystem 90(n) and the network 20. The e-commerce interface 100 is shownto be virtual as can be appreciated by those skilled in the art, as itmay be implemented on one or more computing machines that are separatefrom the e-commerce interface 100 but connected to it. The e-commerceinterface 100 is connected internally or externally to virtualperformance data storage 200 and a wide area network 20, which in aparticular embodiment is the Internet. The system 10 also includes atleast one search engine site 50(n) on which a customer procurementdevice may be obtained The search engine site 50(n) may include physicalor virtual computation 60(n). The search engine site 50(n) is connectedto the network 20 through a connection 22(n). The system includes one ormore optional vendors 30(n), with a virtual computation device 35(n)connected through connection 32(n). An optional consumer purchaser 80(n)may also be part of the system and connected to the network 20 throughconnection 82(n).

FIG. 4 is a simplified illustration of an individual user/bidder system90(n) as may be used in the present invention. Many variations of thestation 90 may be implemented as can be appreciated by those skilled inthe art. The user system 90(n) includes a computation device 98(n) whichcan be one or more computers or part of a computer. The computationdevice 98 is connected to an optional user interface 97(n), which may bea personal computer or workstation through an internal or external busor communication line 91(n). Optionally, there can be individual oramalgamated product servers or databases 92(n,n), which may keepinventory, pricing, availability, shipping costs and other informationupdated. These servers or databases 92(n,n) may be each single ormultiple computational devices or all included as part of a singlevirtual machine and part of a larger computing machine. A financialengine/database 95(n) may be part of the computation device 98(n) or aseparate computation device or computer. A user 96(n) may be a person, agroup of people, an e-commerce system, a computer or automated system orany combination thereof. The connection to the e-commerce interface 100is provided by virtual connection 94(n). Virtual connection 94 may beany combination of internal buses, external buses, communication lines(Ethernet, T1), or software links and may overlap with many otherconnection structures. These structures are shown to be virtual and maybe have physical embodiments that that are implemented in a variety ofways. E-commerce interface components which are local or particular to auser system 90(n) are indicated by 100(n).

FIG. 5A is a simplified block diagram of the e-commerce interface 100 asmay be implemented in the present invention. Once again the parts areshown to be virtual and may be embodied and executed on one or anynumber of computing devices. The e-commerce interface 100 is run on avirtual implementation computer 250, which can include real or virtualstorage 200, which is used to store the performance of customerprocurement devices for various purchases on one or more search engines50(n). The e-commerce interface 100 is connected to the virtual storage200 through a communication system 190, which may be an internal orexternal bus or a network or other communication line, such as T1,Ethernet, etc. The global tool 185 may be the virtual computation enginewhich collects data and executes the computational instructions in oneembodiment. The connection interface 105 virtually or physicallyconnects the global 185 and product 150(n) tools to one or morecomputation devices 98(n) and optionally the financial engine 95 andnetwork 20. The e-commerce interface may also include optional producttools 150(n) which may be for individual or set of products lines. Assuch, they may be linked to the individual product databases 92(n,n) inthe user systems 90(n), but they are not required to be linked. Virtualdata link 160 may be part of the virtual connection 94 or thecommunication system 190 depending on the implementation of theinvention. Optional intelligence module 198 may be included in thevirtual implementation computer 250 or as part of the e-commerceinterface 100. In a preferred embodiment the e-commerce interface 100has a local implementation module 199(n), of which a part areinstructions which may be executed on user system computation device98(n) with access via virtual connection 94 to the e-commerce interface100 over a network. This is shown in FIG. 5B.

FIG. 6 shows a simplified schematic of the local portion of ane-commerce interface 100(n) as would be used for multiple relatedproducts 150(a) . . . 150(z). As mentioned above, the product databases92(n,n) in the user station 90(n) may be directly or virtually linkedwith the optional individual product tools 150(n, n) in the e-commerceinterface 100(n).

FIG. 7 shows a simplified illustration of a first embodiment of theinvention as may be used in a typical keyword procurement scenario. Inthe illustration, there are 4 bidder systems 90(1) . . . 90(4) for akeyword on a single search engine site A 50. To illustrate the flow ofinformation, inquiries or bids from bidders/users come into the searchengine site 50 through communication in route 23 and informationreturning to the bidders/users returns through communication out route24. User systems 90(3) and 90(2) have access to an e-commerce system100(3) and 100(2) as contemplated by the present invention. The accessmay be either direct or virtual.

For example, the e-commerce system 100 could be accessed as asubscription service over a private or public network and either run ona central server or a java virtual machine at the individual biddingsystems 90(n) or a combination thereof.

FIG. 8 represents a “dutch” auction embodiment of the present inventionshown in FIG. 7. The dutch auction has a blind single-bid system inwhich the highest bidder simply gets the highest position, secondhighest bidder gets the second position and so forth. Each user 90(n)supplies an individual bid 99(n) via the network 20 and connections22(n) to the single site selling the keyword 50. E-commerce interfaces100(n) supply the recommended bidding price based on the computation toeach user system 90(n). The recommended bid 101(n) can be automaticallysupplied as the individual bid 99(n) to the site 50, or a human orcomputer user may screen it and accordingly or post it, allowing for arange of optional automation options. In the shown embodiment the bidsare placed in a virtual bid collector 55, which may be on the site 50selling the keyword or on another e-commerce processing site (notshown). The bids 99(n) are posted and the winner 99(2), in this case,gets position 1, 99(3) gets position 2, etc. The virtual bid cutoff 985represents where the minimum bid lies to get any exposure or procurement(in this case three placements are offered). As can be appreciated,there could be a single exposure or any number of positions being bidfor a keyword or other customer procurement device on search engine site50.

FIG. 9 represents a multiple bid, timed auction scenario in the presentinvention in FIG. 7 (“english” auction). In this illustration the bids99(n) are placed in the bid collector 55. However, at time t(2), thebids are posted at virtual location 980 so that the users/bidders 90(n)may access the other bids. The e-commerce interface 100(n) can accessthis location 980 in order to re-compute an appropriate bid for thecustomer procurement device. Obviously, this process may occur once ormany times as the rules of the auction may vary. At timet(z-(increment)), the bids will become final. In the illustration,e-commerce interface 100(2) has determined that user/bidder 90(2) shouldno longer be involved in the bidding and this is indicated by an “X.”However the three other users all submit final bids 99(n′).

Referring now to the flowchart represented in FIG. 10, a simplifieddepiction of the method 1000 for practicing an embodiment of the presentinvention is described. In step 1010 available keywords and potentialpermutations are determined either by a user or a machine. Such a stepcould simply be performed manually, or could be an automatic search runby the e-commerce interface 100 or another program on the usercomputation device 98(n). The site 50 on which the keyword orpermutation is found is accessed in step 1020. Steps 1010 and 1020 maybe performed in either order. In step 1030 the e-commerce interface 100then determines whether performance data is available for the site 50.The performance data may be available from the site itself 50, in whichcase it is loaded into the e-commerce interface 100 in step 1070. If notavailable, the e-commerce interface 100 accesses a performance databasein step 1050, either created by a third party or through amalgamateddata collected by one or more e-commerce interface 100 transactions. Itmay also be stored on the virtual storage device 200, which may beaccessible as part of a subscription service or provided as part of thee-commerce interface 100 with optional levels of access.

Simultaneously while the above steps are being performed, the auctiondata is accessed in step 1024, and the pricing or other offers (in anenglish auction) are accessed and loaded into the e-commerce interface100 in step 1026. Optionally, the system can access pricing and/oroffers on available permutations of the keyword in step 1028, ifappropriate.

In step 1100, the accounting information on the target product or groupof products is accessed by the e-commerce interface 100. Thisinformation may be included in the e-commerce interface 100 orcalculated and accessed by the user's accounting package or financialengine/database 95. Depending on the structure of the entity, thisinformation may be stored and computed on the individual product orproduct subset servers 92(n) or in the product tools 150(n).

In step 1200, the target margin is loaded into the system. This step mayhappen out of sequence as the determination of the target margin in step1150 may be time independent of some of the other steps as inpre-determined. Choosing a target margin may be as simple as a mandatefrom an officer of the company and stored in the financial engine 95 andloaded in step 1150. The target margin may also be entered by a humanuser for each relevant event, such as an auction or at particulardiscrete times like calendared or fiscally-related events, ifappropriate. In step 1300 (discussed below), the e-commerce interface100 processes the site 50 performance data, target margin, keywordpricing, accounting information, and global and product variables toprovide the user (machine or human) with a target price in step 1090. Inoptional step 1500, the e-commerce interface 100 checks to make surethat the keyword bid is appropriate before submitting as a bid it instep 1600. These steps may be included as part of the optional automatedkeyword bidding embodiment described below and shown in FIG. 21.

In the particular embodiment shown, a non-sequential and independentstep, step 1150, a field is dedicated to what percentage the user iswilling to spend as a variable expense of advertising (VAREXP) or whatnet margins (NETMAR) the user desires. The generation of these variablesis discussed below in detail.

FIG. 11 shows a method 1300 for dynamically setting the target cost of aclick-through in a particular embodiment. In step 2010, the e-commerceinterface 100 determines a net margin from a gross margin (GM) fromaccessed information including: price of a product (PRICE); wholesaleprice of product (COGS); gross margin (GRSMGN) calculated from the PRICEand COGS.In step 2020, the (NETMAR) net margin (or other appropriateaccounting benchmark as discussed below) is calculated via an importfrom the company's accounting package which may be executed on thefinancial engine 95 in step 2025. An accounting package may also resideas part of the functionality of the-e-commerce package 100, eithercentrally 100 or locally 100(n)) or simply reside as a fixed field inthe local e-commerce interface 100(n) for simplification. This step maybe practiced with variation without departing from the scope of theinvention. For example, the financial engine 95 may track inventory andreduce price based on aging products, and, therefore, the product subsetservers 92(n) are in communication with the accounting package 95, whichupdates the pricing and entity's financial records (not shown) andreturns the new pricing data to the product subset servers 92(n).Although it is not important to the invention how such updating andinternal pricing are accomplished, it is contemplated that thee-commerce interface 100 and in particular the global tool 185 havespeedy access to the information in both of these virtual structures92(n) and 95 (which may be the same structure) in order to generatetimely information. Of course, for some entities the use of the globaltool 185 may use unnecessary computing resources when In step 2050 areal-time or near real-time evaluation of the real cost of a clickthrough at a customer procurement device inventory tool (ad inventorytool) is accessed and evaluated.

These ad inventory tools may be like those included in such searchengines as Overture.TM., Google.TM., LookSmart.TM., FindWhat or otherappropriate site 50. The real-time evaluation may exist in alternateembodiments either as an automated tool to log in to the PaidPerformance.RTM. interface or equivalent, which is accessible by thee-commerce interface 100, or through a humanly or machine entered fieldfor static pricing (STATPRICE). Step 1050 is one way in which this maybe provided as well.

In order to assess an outcome variable (OV); a series of optional usercontingency variables and evaluations CV(X) may be added in step 2060 etseq. if they are warranted. These pricing calculation factors mayinclude choosing whether the controlling parameter is a variable expenseof advertising (VAREXP, see above), at steps 2062-2063, or net margin(NETMAR, see above), steps 2064-65.

Whether certain pricing structures will apply in steps 2067-68 isdependent of the controlling parameters for the outcome variable. Otheroptional dynamic pricing factors in the e-commerce interface 100 appliedat this step include: whether different shipping which is based onaccounting different shipping tables and pricing based on shipping costs(SHIPCST), different tax tables for accommodating different pricingstructure (TAXTAB), quantity discounts based on above rule sets(RULEDISC), and up-selling and cross-selling (XSELL) based on rule setswhich are stored either locally or globally or apply at global orproduct levels.

At step 2100 the particular rules are loaded of the particular rules andapplication step for determining a target price this step is describedbelow.

In a particular embodiment of the invention, the user defines much ofthe above and then the automated global tool 185 or one or more producttools 150(n), in real time can either change the bid/cost of aprocurement of a click-through or in an alternate embodiment dynamicallychange the price of the product to accommodate the margin desired on aglobal (NETMAR(global rule) or product level (NETMAR (P1,P2), where P1is a rule for one or more products) basis. The VAREXP or the variableexpense of advertising (VAREXP(global) or VAREXP(P1)), see above) orcost acquisition of customer procurement devices can be used for outcomedetermination and in a particular embodiment is defined on the productlevel (VAREXP(product rule)) by the admin functionality of the usersystem 90(n) or of the e-commerce interface 100. However, it istypically expected that this variable would be mandated by a VP of salesor a CFO on a global or product level basis.

In an alternate embodiment of the present invention the result is thatthe e-commerce interface 100 may also dynamically present a unique priceto the consumer, as the consumer has a history of tolerating analternate pricing structure (consumer dependent pricing structure),which can be based on innumerable parameters such as state, zip, title,etc. as there many types of these alternate pricing structures which canbe chosen to implement dynamic pricing. If it is determined thatalternate pricing structures apply in step 2080, the particular detailsare indicated in step 2085. These is factored into the dynamic pricingsystem at step 2100 (described below) based on the user preferences foralternate pricing mechanisms.

Of course, in a preferred embodiment of the present invention isprimarily designed to assist in the acquisition of customer procurementdevices by providing dynamic pricing (price target ranges) to assist inthe acquisition of such devices. In alternate embodiments, the presentinvention can assess pricing of one or a define set of products based onthe cost of advertising (VAREXP) or using the cost of customerprocurement device acquisition simply as part of the dynamic pricingmodel. As can be appreciated by those skilled in the art, a set ofrelated products may or not be connected through acquisition ofdifferent customer procurement devices and thus may have differentpricing considerations for each acquisition. This is shown in FIG. 12, avirtual product pricing relationship table, 950 which may be storelocally or in virtual storage 200.

Referring now to FIG. 13, step 2100 is shown in greater detail as tosteps in a particular embodiment for dynamically determining a targetprice. The algorithms that have been determined to apply for the pricingrules are loaded in step 2110. It is determined if consumer pricingfactors apply in step 2115 and if so, they are loaded in step 2117. Anyconsumer pricing factors (discussed above) may optionally be determinedby determining market conditions in step 2148, if such conditions areavailable for pricing. A preliminary target price is computed in step2120. In step 2145 it is determined if a decision support factor (DSF)is to be applied. If so, in step 2147 the interface 100 determineswhether market conditions apply to the DSF or are available. If so, themarket conditions are located in step 2148. In step 2149, the interface100 then determines if the market conditions warrant application ofmarket-based DSFs (discussed below), and if so, in step 2150 themarket-based DSFs are loaded into the system. Other accounting andfinancial rules, which are not based on the market conditions, may beapplied at step 2155. In step 2190, the interface 100 determines whetherthe target price meets the DSF rules or consuming pricing factors. Theinterface can revert to step 2115 if new consumer pricing factors needto be loaded or if DSFs indicate an unacceptable situation, can warn theuser in step 2195. If all DSFs are satisfied, the target is submitted instep 2199.

Such decision support factors may take into account both global andspecific accounting and marketing principles and range from the simpleto the complex. Such decision support factors may also provide the userwith adequate warnings when the advertising procurement or productpricing is not within a set of acceptable parameters. For example, anovice may wish to sell 100 G's at $20.00 each with a profit of $15 persale (expected profit $1,500). The cost of a click-though may be $0.25,which appears reasonable to the novice. However, the performance toolindicates to the e-commerce interface that over an hour there will be10,000 click-throughs ($2,500!) and a conversion rate of 1:50. Thus, thenovice will be purchasing enough performance over an hour to sell 200and will not be able to derive any profit past the sale of the last ofthe 100th item. Thus, there is expected to be a $1,000 loss, even thoughselling 200 would result in a profit of $3,000. While this is arelatively simple example of a decision support factor being applied,the dynamic relationship between open-ended advertising costs, productpricing mechanisms, and generating market share provided by the presentinvention provides much-needed support not contemplated by any relevantart.

In a simplified sample procurement engine method implemented in oneembodiment of the invention, a method 3000 for real time or near realtime application of the e-commerce dynamic pricing tool is shown in FIG.14. In this example, the auction for keywords is taking place for fiveminutes and will accept bids up to the closing time. It also posts allbids in five second increments. The time intervals from t1 to t5 givenbelow are examples and not meant to indicate that the e-commerceinterface 100 is limited to specific time intervals. However, as can beappreciated by those skilled in the art, there may be a calculation forstrategic timing of specific acts, like evaluating and placing bids, forwhich the e-commerce interface 100 may be particularly well suited forboth evaluation and execution purposes and an optional part of analternate embodiment. The following example also illustrates thesuitability for the present invention in such a time-constrainedacquisition environment.

At time t1 (−05:00), the customer procurement device engine informs auser that desired keywords ($A,$B) are being auctioned for time period(Y to Y+INTERVAL). The bidding of click-throughs starts at $0.05, whichthe e-commerce interface 100 monitors.

At time t2 (−04:25), the e-commerce interface 100 accesses anyperformance data available either through the search engine sites 50 orthrough the accumulated data stored in the virtual storage 200. Also, attime t2 the financial engine 95 is accessed for relevant information ona target product or set of products. The individual product databases92(n) may have to be accessed at this time as well, if there is not acontinuous update. The e-commerce interface 100 also screens forpotential permutations or variations of the keyword that may beavailable and beneficial to the user. This aspect of the invention isdiscussed below.

For auctions that use the open bid, like the english auction model, atthis (or another) time interval, the e-commerce interface 100 accessesthe early bids for the keyword. Such early bids may provide the globaltool 185 or product tools 150(n) with valuable information in computingthe target keyword price range. In particular embodiments, previous bidinformation may be available, not only as absolute pricing information,but in the timed bidding aspect as well. Thus, the e-commerce interface100 has optional built-in artificial intelligence module 198, of whichone of the functions is detecting pattern to (timed) auctions anddeveloping a rule in calculating the pricing target. In the backgroundsection, there are several patents and publications relating toelectronic auctions are discussed, and those patents and publicationsare hereby incorporated by reference for all purposes, and in particularto illustrate the details of electronic auction and relatedtransactions.

At time t3A (−3:00), the e-commerce interface 100 prompts the user 96(or user/machine) for any missing information that must be entered. Ifthe user 96 cannot enter the information, the interface 100 will havestanding or contingency instructions as to whether it should continue inthe keyword auction.

If the bidding is to continue, at time t3B (−2:45), the e-commerceinterface 100 determines whether a bid is within range of the calculatedtarget price. If it is within range, then the bid is either passed alongto the user for bidding, or is posted to the auction location. Thepermission may include any pre-registration features that auctionparticipation requires such as registering a credit card or providingother personal or business information. Although it is expected thatmany users will have pre-registered, there may be advantages with notbeing pre-registered, as can be appreciated. Permission steps may alsoinclude any time of authorization by the user or officers, such as acomptroller, who may be monitoring the bidding manually orautomatically.

If the bid is not within the target range, the user is informed that thebid has exceeded the target range. The user or other authorizer may thenchoose to override the target range and place a bid. Optionally, the bidmay be entered manually and directly posting or the e-commerce interface100 via the global tool 185 or product tools 150(n) which can adjust thenew bid incrementally or by other factors back to the permission stage.

At time t4 (−1:30), if permission is granted, the initial bid is placedat the bid posting area 55, which may be on the search engine server orcomputing machine 60 or in another location, such as the transactionserver for the auction. Any posted bids are monitored until the targetending time (t5), when the e-commerce interface 100 must assist the userwith a final bid decision. Thus, all bids until the time t5-evaluationtime are evaluated by the interface 100.

Also, at time t4, if permission is not granted, the data regarding thebids and target range are recorded by the e-commerce interface 100 asmuch as would be possible for future use and may proceed to the nextavailable advertising sale. For example, an optional aspect to theinvention is that it will gather data on customer procurement tools evenwhen acquisition fails and store locally or globally in the virtualstorage 200.

At time t5 (−0:30), with very little time left to go in the auction, thee-commerce interface 100 determines whether a new bid is warranted basedon any new information, particularly new bids. If a new bid is warrantedand still within the target range then the user is informed and/or thebid is posted to the bid posting area 55. If the bid is not within rangeany more, the e-commerce interface can opt out and simply record thedata from the failure or prompt the user to determine whether the userwants an override. Of course, as can be appreciated the time intervalsmay be constructed to allow for various user options. Thus, in anembodiment where a user 96 manually posts a bid, there would be moretime allowed than 30 seconds. Whether or not the customer procurementtool is acquired, the e-commerce interface 100 will record and store thedata in a preferred embodiment for future decision support. However, ifthe customer procurement tool is acquired, other monitoring algorithmsmay be implemented in order to accurately determine value andperformance of customer procurement devices.

In a highly simplified scenario, the following numbers may be includedin a simplified calculation of the present invention: For seller A, onSunday, from 1-5 pm, the keyword “skin care products” generates 17,500click-throughs, 796 customers who purchase $4,117 worth of merchandise.525 of the 796 sales were for skin care products.

1TABLE 1.1 Sample variables for calculating the relative real cost of aclick-through. Variable Definition Example Previous Last procurement of“keyword” $A=0.17 per click- Price through Adj. Factor Time periodnormalization (Sunday 1-5pm) factors present? Y=N*1.17 CT Rate Number ofclick−17,500/4 hrs=throughs per hour 4375 cts/hr Conv. Rate Customerprocurement 22:1 (actual purchase) to click-through ratio Rev. per SaleGross revenue per sale $5.17 Ret. Cust Return customers=12.7% (per 6(from click-through sale) months) Ret. Cust/CT Return customer=5% (per 6through click-throughs months) Keywrd/Sale Customers who bought525/796=66% product products related to the keyword (if more than oneset of products)

In this table the Sunday 1-5 pm slot gets 17% more traffic than theaverage daytime amount of traffic. Thus, the search engine auction forthe skin care products keyword may adjust the lowest bidding price.However, the search engine may not adjust pricing at all, and thee-commerce interface 100 will have to account for such factors (ifexecuted by the user) in order to accurately bid on a keyword. Thistable also represents previous data of one user during one time period.As can be appreciated by those skilled in the art, the collection ofdata for multiple entities or search engines for multiple keywordperformances will require a great deal of computing power and datastorage. The present invention contemplates that providing optionalaccesses by individual e-commerce interfaces 100 to a centralized datastorage 200 and virtual implementation computing system 250 may beadvantageous to all embodiments of the invention whether virtual orphysical and regardless of location.

The above table is representative of summary data that may be providedby the search engine site, or collected by the present invention foreach search engine or each user. It is also contemplated that a pool ofusers of the present invention collect their data in a central datastorage such that the set of customers has access to alternate or betterinformation regarding performance than the search engines.

Varying levels of data access may also be implemented in particularembodiments.

Table 1.2 Sample calculations used from variables in determiningperformance

CALC. DEFINITION EXAMPLE

GR/CT Gross revenue per click-through $4117/17,500

Acquisition Cost of any new customer sale PP of click-throughs(0.17*22)−12.7% (returning customer)=$3.29

Target/CT Margin of primary product or set of products for keyword perclick-through ($1.27*450)/17500

Crossover Percentage of sale for unrelated prod. from a keyword “skincare”=34% xsell@$6.17 per sale

Of course, these are highly simplified factors and calculations and arejust some examples of how the present invention may use such variablesand support factors to provide a target price to the user. As can beappreciated by those skilled in the art, there are numerous otherfactors that can be amalgamated into the decision many of which arelisted in the specification. The specific set of variables that isapplied will depend on many factors chosen by the user of the e-commerceinterface 100 and the structure and implementation of the presentinvention. For example, global rules are more likely applied toembodiments of the invention that take the form of a subscriptionservice.

Thus, the present invention contemplates that calculating the cost of aclick--though will need to account for all the financial informationrelated to a product and all relevant pricing information. There is noreason that the e-commerce interface 100, which includes the global tool185 and product tools 150(n), cannot pre-configure or calculate much ofthis needed information in order to better conduct real-time or nearreal-time analysis while using less computer resources at time-criticalperiods.

A sample of database items from an accounting package executed on thefinancial engine 95 would be processed before auctions in order togenerate any pre-configured parameters.

As stated above, rules for pricing based on the information may beapplied in various ways without departing from the spirit of the presentinvention. Rules may be applied from a central location for asubscription service embodiment generated by virtual implementationcomputer 250 or applied on the user's computation device 98(n) in anembodiment of the invention that can be executed locally or both. Rulesets may be defined by both general principles of transactions andcustomization routines specific to particular entities. In the simplestembodiment the global tool 185 will apply a set of rules, which can bechosen by a user 96 in a setup configuration. Of course, the rule setswill change for each individual user 96 based on data captured andanalyzed from previous customer procurement acquisition attempts byeither the individual or collectively.

Table 1.3 Sample application of rules for pricing products

Scenario Rules for keyword procurement/product pricing

Pricing of one single item F Rule 1(A)

Pricing of multiple single items F (<2) Rule 1 (B)=15% discount

Pricing of multiple single items F (>25) Rule 1 (C)=15%+0.1 discountover 25 ct.

Pricing of subset A (D,E,F,G) of total inventory multiple items Rule2(B)=average of price of each item plus 15% discount

Pricing of any number of each item in total inventory (D-H) Rule (3,Allsale)=only count average of 5 most expensive items and subtract shippingcosts The above table provides for a highly simplified rule applicationby the global or individual product tools 150(n). Obviously, the morethe sales of one or more products the less the relative real cost of aclick-through. However, there are factors that may optionally beaccounted for differently for each user of the e-commerce interface 100.For example in Rule 3, “all sale” would make sense for a large entitythat had a large price range of products and low shipping costs andwhere only the higher priced items should be included in the calculationof the advertising procurement target range. However, Rule 1 (B) wouldbe more applicable to a small entity with large shipping costs and smallmargin on product F (perhaps even a loss). Thus, the purchase of 24items F does not provide the entity with a large profit over the sale of2 and no additional discount is applied until 25, in which the shippingcosts drop enough to make a profit, when Rule 1(C) would apply. Thus,Rule 1 (B) may be a good rule application where a site uses F as itssignature product or customer draw to the website in order to sell moreprofitable products.

As stated above, it is not necessary for the invention to be limited tothe pricing of advertising because the invention works in inverse aswell to dynamically adjust the price of a single product, multiplesingle products or multiple sales of plural products. Thus, the price ofF, which is the signature product of the company, and is sold at a loss,can be dynamically determined by the real cost of the click-through. Thereal cost can be constantly updated to improve the profit generated froma click-through or to prevent too many losses. For example, aclick-through costs $1.00 and the profit margin of product F beforeadvertising is $0.25. Thus for a click-through/conversion ratio of 10:1for each single F sold, the more the company loses $9.75. However, if apurchaser buys 40 Fs at time, the company breaks even. Thus, thee-commerce interface will determine that if the click through/conversionration improves or the average sale of F (or related and more profitableproducts) increases, the more the company can afford to lower the priceof F based on a volume discount. However, if consumers are onlypurchasing a single F at a loss of $9.75 per sale, the e-commerceinterface 100 can adjust the price such that losses are minimized.

The price determination may also account for other market factors basedon usage, timing, etc., and is loaded at step 2150 and applied in step2190. For example, a problem with any type of English auction bidding isthat the experts generally submit bids at the last minute, hiding theirtrue intentions and expert bidding from less experienced entities. Thus,less experienced bidders may overbid, driving up the priceunnecessarily. Dutch auctions may eliminate the time pressure aspectpresent in the English auction for a keyword that drives the priceupward toward the end of the bidding. Step 2149 may detect the situationand step 2150 applies a rule that 50 may account for this spike inkeyword bidding and advise the user accordingly in step 2190. As such,the e-commerce interface 100 will have intelligence capabilities builtinto the global tool 185 and product tools 150(n).

As can be appreciated by those skilled in the art, the performance of aclick-through has many variables involved not the least of which isoften dependent on the search engine site itself. Of course, the metricsaccumulated by the search engines themselves may be important criteriain showing the true value of a “click through” or an “impression” (orother advertising mechanism). As such, the present invention helps auser to successfully analyze of information controlled by the searchengine services and gives a bidder for a customer procurement devicereal-time assistance in acquiring such advertising with all availableperformance data. Of course, payment for a “click-through” may be afairly good indicator of how many people are responding to anadvertisement, but really does not measure the cost-effectiveness intotal. To some degree there may be some uncertainty built into Internetadvertising performance measures, but the present invention can accountfor variances by accumulating and storing information for use in thee-commerce interface 100. Such data may be acquired in a single locationor virtually and disseminated in the e-commerce calculation) as part ofan alternate embodiment of the invention. As such, comparisons betweensearch sites, keyword elements and permutations, and variations, amongother factors, have already been discussed above.

Referring now to FIG. 15, a multiple search engine embodiment of theinvention is shown. This embodiment simply has multiple search engines50(1) . . . 50(n) on which keywords or other customer procurementdevices may be acquired. This embodiment is similar to the single searchengine keyword procurement embodiment described in FIG. 3, except thatthe virtual performance data storage 200 will have an inter-sitecomparison module 998. This module will access and/or store individualperformance data-related sites and keywords and related information. Asimplified example is shown in the table of FIG. 16, which compares thepricing and performance characteristics for three search engines 50(1) .. . 50(3), and is a table showing a sample database of table query aswould be used by an embodiment of the present invention as used in themultiple search engine keyword acquisition shown. As can be appreciatedby those skilled in the art, the factors used in determining anappropriate auction price may vary widely and take in account time ofday, type of word, etc.

Referring now to FIG. 17, an embodiment of the present invention whichfactors in keyword “elements” for acquisition is shown. For example,entity A wishes to purchase “discount Caribbean cruises,” which hasproven to be an effective keyword tool for entity A. However, due to arecent revision of a couple of keyword systems, the desired keywordshave been divided into different categories. Thus, “discount cruises”and “discount Caribbean” are available. However, e-commerce interface100 has data that most of the keyword searches for cruises are in factlooking to go on a Caribbean cruise when purchased in January. Thus, theunavailability and competition for “discount cruises” may be high, butthe purchase of the term “discount Caribbean” may be acquired at betterperformance-to-price ratios. The table shown in FIG. 18 is an example ofhow this calculation may be made.

Referring now to FIGS. 19-20, yet another embodiment of the inventionthat contemplates possible multiple search engines, key wordsegmentation and/or permutations is shown. By “permutations” at leasttwo different types of things are meant. First, there are key synonymvariations on the target keyword that are valuable for an entity whichmay recognize that targeting a small group of searches of a certain typecan lead to improved sales. Second, as is common in keyword searching,spelling errors are fairly common in using search engines, and suchmisspellings may often be a valuable capture for an entity looking tocapitalize on such exposure.

Table 2.1 Sample keyword permutations and weighting factors (type 1)

Keyword Synonyms Relative Incidence per Target (/100) RelativePerformance to Target (/1) Search Eng.

Adjustment Price Factor for Acquisition

“dermatology” 221.3 N/A Apply rule X

“dry skin treatment” 34.75 N/A Apply rule Y

“skin care” 55.65 N/A Apply rule Y

“dermatologist approved” 63.2 N/A Apply rule Z

Of course, rules X, Y, and Z are hypothetical financially basedalgorithms that are applied based on the target needs of the users. Forexample, rule Z may apply in situations where the incidence of thealternate keyword is very low (0.06), but the performance is very high(over 3 times normal). Thus, the value of this keyword may be higherbased on traffic factors, like time of day, day of week, sophisticationof the search engine, etc. Rules X and Y may be more straightforward,possibly even linear pricing factors. Furthermore, there is not enoughdata on this table to account for any search engine factor, but afterthe purchase of a keyword, or even through the accumulation of data bythe search engine 50 itself, the data may become available. As statedabove, this data may be available as part of a sales tool, or as part ofa subscription or downloadable data service provided as a supplement tothe present invention.

Table 2.2 Sample keyword permutations and weighting factors (type II)

Keyword

Variations Relative Incidence per Target (/100) Relative Performance toTarget Price Factor for Acquisition Search Eng. Factor

“dermatology” 2.11.1 Rule A N/A

“dermoltgy” .7.87 Rule A N/A

“dirmotology” .4.89 Rule C N/A

“dermotological” .34.05 Rule B N/A

The above table acts very much like table 2.1 in that it accounts forthe past performance of mistaken spellings of the target keyword inorder to provide a value for acquiring a misspelled keyword. Of course,not all keyword auctions or sales may offer the kinds of variationssales that are discussed in this specification. However, search enginesand other advertisers may recognize the value of these variations eitherpackaged as a bundle with the target keyword or purchased for “residual”value by other entities. Certainly, a purchaser of a bundle of keywords,which include synonyms and misspellings, may resell one or more of theset to another entity. The present invention contemplates the resale ofsuch keywords in order to maximize the value to a user. For example, apurchaser who buys words A, A′, and A″ for 32 cents a click-through mayfind that keyword A and variation A″ are valuable for customerprocurement and sales of product X1, but A′ is not useful. Thus thepurchaser desires to sell A′ to a subpurchaser who may benefit fromusing it in the sale of products Y1 and Z1.

In a preferred embodiment, the present invention contemplates the keyword auction as the primary use of the method by which the presentinvention operates.

However, as can be appreciated by those skilled in the art, other typesof purchases for various types of customer procurement mechanisms may beacquired though the teachings of the present invention.

Referring now to FIG. 21 an automated method for the customerprocurement device acquisition system 2700 is shown. The automatedcustomer procurement device has a scheduling and notification module 300as a virtual part of e-commerce interface 100. The scheduling andnotification module 300 may be physically located on the computingdevice. The scheduling and notification module 300 can self-activate instep 2710 or monitor keyword selling sites discretely or continuously instep 2720. If the module finds that a target keyword is available instep 2750, then the method shown and described in FIG. 10 above isperformed in step 2760. If the system is not deactivated in step 2762 itreturns to the monitoring state. Simultaneously, if the system was notsuccessful in step 2770, it performs a notification and adjustment instep 2780. If it was successful it records any performance detectionprograms in step 2790 before being reactivated.

Referring now to FIG. 22, a cross-selling, up-selling and/or agencysystem 5000 using the present invention is shown and includes one ormore vendor systems 70(n) and one or more buyer systems 40(n). Thee-commerce interface 100 advises the user 90 who is now brokering bothbetween one or more vendors 70(n) and purchasers 40(n) as well asprocuring Internet advertising devices on search engines 50 at the sametime. As can be appreciated, the complexity of such dynamic transactionsalmost requires the dynamic pricing e-commerce interface 100 to maximizepotential profits and assist with the pricing.

FIG. 24 illustrates an alternate embodiment of the invention in whichthe e-commerce channel advertising procurement and analysis system cansupport other sales channels, such as 1-800 telephone numbers. Thisparticular embodiment may be more effective in assisting entities withitems that are traditionally sold by toll-free sales as opposed to pureinternet sales. It also provides for cooperative opportunities in whichdelivery systems may be more effective spread out among smaller regionalsales coverage, such as flower delivery.

FIG. 24 shows some optional features of the alternate sales channeladvertising channel system as well. An advertisement or a product orservice available through a 1-800 sales channel, includes anidentification code, whether in alpha-numeric or code word (not shown).The advertisement, in a preferred embodiment, is most likely viewed overthe Internet, but the embodiments of the invention are not limited tothe Internet advertising and the identification code could easily betransmitted by television, radio, press, billboard, sandwich board orother traditional media. The 1800 call is placed through a telephone orcellphone and most likely routed through an SMS database for 1800 numberrouting. In alternate embodiments the call may be routed though othertypes of programmable telephonic routing. In the diagram, the call isrouted through the SMS database rules to optional intermediate relays orrouters IL STATIONS that may be part of the public telephonic network,but also may be privately operated. The call is routed via theprogrammed rules, which will be discussed in below in FIGS. 25-27,through a telecommunications network, or alternately through apacketized network (such as Voice over IP) to the appropriately chosenvendors (vendor 1, NYC), (vendor 2, LA), or (vendor 3, Minneapolis),where the call is processed by the vendor.

The telephonic vendor (vendors 1, 2, and 3) who processes the call mayallow for the ID to be placed into the phone prior to processing thecall, thus the ID can be tracked via various method including routedwith the call. The process of identification code entry for telephonicinterfaces for internal tracking purposes is disclosed by a family ofpatents issued to Ronald A. Katz, Licensing Partners and include U.S.Pat. Nos. 6,148,065, 5,815,551, 5,561,707, 5,684,863, entitledTELEPHONIC-INTEFERFACE STATISTICAL ANALYSIS SYSTEM and U.S. Pat. Nos.5,787,156, 6,044,135, 6,424,073, 5,365,575 entitled TELEPHONIC-INTERFACELOTTERY SYSTEM and U.S. Pat. Nos. 5,553,120, 5,349,633, 5,218,631,6,151,387, entitled TELEPHONIC-INTERFACE GAME CONTROL SYSTEM. Katz alsodiscloses other types of tracking for sales purposes in U.S. Pat. No.6,055,513 entitled METHODS and APPARATUS FOR INTELLIGENT SELECTION OFGOODS and SERVICES in TELEPHONIC and ELECTRONIC COMMERCE. All of thesepatent disclosures are incorporated herein by reference. However, theseare a few disclosures of the techniques available to process an IDnumber through a 1800 call and may not be implemented at all in any formin some embodiments of the present invention.

Alternately, the ID may be entered at the intermediate relays ILSTATIONS and appropriate tracked through the process of the call.

The ID data is entered into the vendors computer system or a networkedsystem which may be a specialized computer entry system for purposed oftracking information (shown in FIG. 28) labeled as ETRAC(.TM.)

In one embodiment, the invention includes a method for routing acustomer call to a particular vendor comprises the steps of providing aphone number to a customer, wherein the number is linked with aplurality of “consumer category codes,” and wherein said customer makessaid customer call by dialing the phone and entering one of theplurality of “consumer category codes;” determining which of saidplurality of consumer category codes is entered by said customer;associating said customer call with a consumer category based on whichof the plurality of consumer category codes is entered; creating aconsumer category database, wherein the consumer category databasecontains at least one vendor related with said consumer category;selecting one of said at least one vendor to produce the particularvendor of choice, wherein said particular vendor is selected based on abidding factor, and wherein the bidding factor comprises a bid made to aprovider of said phone number; and displaying a source to the particularvendor, wherein the source provides at least some detail on how saidphone number is provided to the customer.

Optional features include where the bidding factor further comprises apreferred vendor status (based on a winning or weighted bid), whereinthe bidding factor further comprises a geographical limiter; where thebidding factor further comprises availability of vendor in said categorydatabase; where the bidding factor further comprises a financial rangeprovided by the customer; where the bidding factor further comprises akeyword distinction selected by said particular vendor

Optional features regarding the consumer category include where theconsumer category contains a geographical limitation parameter; wherethe consumer category codes provide a geographical limitation to thegeographical limitation parameter; where the customer provides ageographical limitation to the geographical limitation parameter or asituation where the customer enters a plurality of the consumer categorycodes.

In one variation, the phone number and at least one of the plurality ofconsumer category codes is provided to said customer via anadvertisement. In another the source details said advertisement wherethe details comprise past consumer call made because of saidadvertisement. The advertisement or customer call is via the Internet,and the customer call is dialed automatically and at least one of saidplurality of consumer category codes is entered automatically by saidcustomer choosing said advertisement.

FIG. 25 shows the architecture of the procurement system. A group ofcompetitive purchasers PURC POOL, most likely over the internet or otherprivate or semi-private network N (which may be subscription, or aparticular ISP), bid for 1800 call listings or routings based onkeywords for search engines. Thus, the procurement or purchasinginformation data PF or PF′ is passed from the advertising channelprocurement system 100″ to the appropriate level of the telephonic orwide area network, IC or 1800 SMS data.

FIG. 26 shows the representative data flow in the toll-free salesadvertising channel analysis and procurement system. The identificationID-T is broadcast shown as a television or the internet (but not limitedto these media). The ID-T is then passed manually or telephonically (asdiscussed above) to the 1800 control routing which may include the SMSdatabase or be controlled by a private telephonic network. The 1800control routing places the call whether directly or through instructionsto one of a set of vendors (there may not always be multiple vendors)based on the instructions provided by the procurement system (ref 100″in FIG. 25). The ID tracking is then put into the analysis system 100″by automatic or manual means and in some cases a combination (see FIG.28). In the case where a purchaser may dial a sales number, such as a1800 number directly from their computer, the ID-T may be automaticallyrouted through the telephonic system (if it has such capabilities).

FIG. 27 shows the representative functions of the toll-free salesadvertising channel procurement system. The advertising channel analysisand procurement system 100″ may be implemented as discussed above inFIGS. 3-23, but the features in the alternate embodiment include the“weighting” module which affects the procurement of the call procurement

The procurement system may include such mechanisms as randomization inwith or without weighted or contingent factors, such as region, customertype, time, portal used, web surfing behavior (shown in the diamond), orother types of contingent factors that may be used to determine awinning bid for routing the 1800 call to the preferred vendor. In orderto facilitate smooth implementation of this embodiment of the invention,it is contemplated that the 1800 routing device (shown in FIG. 25) willprovide instructions to the telephonic routing database, such as“1800BUYDIAM” will route the call to jewelry B if the call originated inzone 2. The procurement system may behave in much the same way that thee-commerce advertising channel would behave, except that the endprocurement may include the telephonic component in addition to itemssuch as keywords and affiliate tracking.

FIG. 28 shows a sample stand-alone computer solution for the ID entry atthe 1800 or telephonic vendor level. In this case a simplified devicemay be used manually to enter the ID codes which are linked through thenetwork (on site or off), or the telephone system passes the code at thevendor level.

As can be also appreciated by those skilled in the art, while thepresent invention is contemplated in a preferred embodiment to assistthose seeking to acquire keywords for impressions or click-throughs,there are other advertising devices that would be appropriately acquiredin similar environments by the present invention. The present inventionis also dynamic and scalable, as can be appreciated by those skilled inthe art, and can be used by individuals as well as large Internet salesorganizations.

1. A method for routing a customer call to a particular vendorcomprising: providing a phone number to a customer, wherein said numberis linked with a plurality of consumer category codes, and wherein saidcustomer makes said customer call by dialing said phone and entering oneof said plurality of consumer category codes; determining which of saidplurality of consumer category codes is entered by said customer;associating said customer call with a consumer category based on whichof said plurality of consumer category codes is entered; creating aconsumer category database, wherein said consumer category databasecontains at least one vendor related with said consumer category;selecting one of said at least one vendor to produce said particularvendor, wherein said particular vendor is selected based on a biddingfactor, and wherein said bidding factor comprises a bid made to aprovider of said phone number; and displaying a source to saidparticular vendor, wherein said source provides at least some detail onhow said phone number is provided to said customer.
 2. The method asrecited in claim 1, wherein said bidding factor further comprises apreferred vendor status.
 3. The method as recited in claim 1, whereinsaid bidding factor further comprises a geographical limiter.
 4. Themethod as recited in claim 1, wherein said bidding factor furthercomprises availability of vendor in said category database.
 5. Themethod as recited in claim 1, wherein said bidding factor furthercomprises a financial range provided by said customer
 6. The method asrecited in claim 1, wherein said bidding factor further comprises akeyword distinction selected by said particular vendor.
 7. The method asrecited in claim 2, wherein said consumer category contains ageographical limitation parameter.
 8. The method as recited in claim 7,wherein said consumer category codes provide a geographical limitationto said geographical limitation parameter.
 9. The method as recited inclaim 8, wherein said customer provides a geographical limitation tosaid geographical limitation parameter.
 10. The method as recited inclaim 1, wherein said customer enters a plurality of said plurality ofconsumer category codes.
 11. The method as recited in claim 1, whereinsaid customer call is dialed automatically and at least one of saidplurality of consumer category codes is entered automatically by saidcustomer choosing said advertisement.